BMS 3008: Integrated Biomedical Sciences Lecture 3: Experimental Design and Clinical Trials

Part 1: Hypothesis-Driven Laboratory Project

Neural Blast Cell Differentiation Regulation

• Growth factors, as local mediators, regulate cell fate during organism development.

• In embryos, rapid cell growth and proliferation occur with undifferentiated cells.

• In adults, cells face stringent restraints to prevent uncontrolled growth.

• Growth factors are peptides released by signaling cells, impacting target cells.

Regulation of Neural Cell Differentiation

• Several growth factors control neural cell differentiation.

• Neural stem cells differentiate into astrocytes upon growth factor exposure.

Identifying Genes Involved in Differentiation

1. Candidate Approach: Quantitative PCR analyzes genes thought to change with growth factor treatment, but has limited output.

2. Global Analysis: RNA-sequencing (RNA-seq) interrogates all gene expression changes to identify cohorts of genes involved in differentiation.

Principles of RNA-Sequencing

1. Isolate RNA from samples.

2. Fragment RNA into short segments.

3. Convert RNA fragments into cDNA.

Outcomes of RNA Sequencing

• Aligning sequencing reads to the human genome identifies all expressed transcripts (transcriptome).

• Comparing transcriptomes between cell populations (with and without growth factor) reveals global transcriptional changes during differentiation.

• Heatmaps effectively display gene expression changes, with columns as individual replicate samples, genes on the right, and expression levels indicated by color.

PhD Project: Key Regulators of Neural Cell Differentiation

• PhD student James uses RNA-seq to identify genes regulating neural cell differentiation, treating undifferentiated neural cells with and without growth factor.

• He identifies numerous genes with differential expression in response to growth factor treatment.

• Synaptophysin is one such gene.

• The key question is whether the increase in synaptophysin mRNA levels leads to an increase in synaptophysin protein level.

Validating mRNA Levels

• Quantitative RT-PCR validates synaptophysin mRNA levels: isolate RNA, generate cDNA via reverse transcription, and determine cDNA level for sequences of interest via quantitative PCR.

• Comparison of synaptophysin mRNA expression shown via a graph.

Techniques to Assess Synaptophysin Protein Level Changes

1. Western Blotting: Detects protein hybridized to a membrane using antibodies.

2. Immunofluorescence: Detects proteins directly in intact cells using antibodies, providing cellular distribution information.

3. ELISA: Quantifies proteins bound by antibodies on plastic.

4. Flow Cytometry: Quantifies proteins in cells using fluorescently-labeled antibodies (covered in another lecture).

Effect of Growth Factor on Synaptophysin

• Western blot analysis is used to assess synaptophysin protein levels after growth factor treatment.

• Synaptophysin has a molecular weight of 30 kDa.

• $\alpha$-Tubulin is used as a loading control.

Immunofluorescence to Detect Synaptophysin

• Indirect Immunofluorescence

  • Native synaptophysin is detected in cells using a primary antibody that binds to synaptophysin, followed by a secondary antibody with a fluorophore.

  • Advantages: Allows multi-color imaging and preserves protein in physiological state.

  • Disadvantages: Requires a suitable antibody and can be expensive and time-consuming.

• Direct Immunofluorescence

  • Cells are transfected with a plasmid to express a GFP-Synaptophysin fusion protein.

  • Advantages: Quick, allows multi-color imaging, and is cheaper.

  • Disadvantages: Potential signal variation, relies on cell transfectability, and the fluorophore may affect normal protein activity.

Confirming Red Fluorescence as Synaptophysin

1. Perform the experiment in cells lacking synaptophysin expression.

2. Block primary antibody binding with a specific peptide/epitope.

Quantifying Synaptophysin Level Increase with ELISA

• ELISA quantifies synaptophysin level in a complex protein mixture.

• Sandwich ELISA: Cell lysate is added to a vessel containing a capture antibody, which binds to the target protein. Primary and secondary antibodies are added, and the secondary antibody-conjugated enzyme generates a color change proportional to the target protein quantity.

ELISA Procedure

1. Cell lysate added to vessel with capture antibody.

2. Target protein binds to capture antibody.

3. Vessel is washed, and primary antibody is added.

4. Secondary antibody binds to primary antibody.

5. Enzyme activation leads to a color change, indicating protein quantity.

ELISA Quantification

• ELISA is used to quantify synaptophysin levels, using synaptophysin capture and labeling.

• A standard curve is generated using known synaptophysin concentrations.

Preparing for ELISA

• Cell lysate is collected, and protein concentration is measured.

• A specific amount of total protein (e.g., 50 $\mu$g) is required per well.

Dilution Calculations

• Calculations are needed to determine the volume of lysate required to provide the specified amount of protein.

• If the untreated cell lysate concentration is 2.3 mg/ml, the dilution factor and volume required are calculated as follows:

  • Concentration: 2.3 mg/ml = 2300 $\mu$g/ml

  • $\frac{2300 \mu g}{50 \mu g} = 46$ (Dilution Factor)

  • $\frac{1 ml}{46} = 0.0217 ml$ or 21.7 $\mu$l (Volume for 50 $\mu$g)

• Water is added to reach the desired total volume (e.g., 28.3 $\mu$l H2O to reach 50 $\mu$l).

• If the treated cell lysate concentration is 3.7 mg/ml, the dilution factor and volume required are calculated as follows:

  • Concentration: 3.7 mg/ml = 3700 $\mu$g/ml

  • $\frac{3700 \mu g}{50 \mu g} = 74$ (Dilution Factor)

  • $\frac{1 ml}{74} = 0.0135 ml$ or 13.5 $\mu$l (Volume for 50 $\mu$g)

• Water is added to reach the desired total volume (e.g., 36.5 $\mu$l H2O to reach 50 $\mu$l).

ELISA Plate Setup

• Samples and standards are plated in triplicate for accuracy.

• Standards contain known synaptophysin concentrations to generate a standard curve.

ELISA Data Acquisition

• The ELISA plate is read using a spectrophotometer to measure optical density for unknown and standard samples.

• Optical density is directly proportional to protein concentration.

Calculating Synaptophysin Concentration

1. Plot a curve of standard samples (O.D. on y-axis, [Protein] on x-axis).

2. Estimate synaptophysin concentration in the lysates using acquired values.

Data Analysis Example

• Calculate the mean O.D. of unknown samples.

• Plot O.D. against protein concentration to determine the protein concentration of unknowns.

• Example Values

  • Untreated cells = 3 ng/well

  • Treated cells = 71 ng/well

Calculating Synaptophysin per mg of Total Protein

• Determine the amount of synaptophysin per mg of total protein to normalize the data.

• In untreated samples, if 50 $\mu$g total protein contains 3 ng synaptophysin, then the amount of synaptophysin in 1 mg of total protein is:

  • $\frac{1 mg}{50 \mu g}$ or $\frac{1000 \mu g}{50 \mu g}$ = 20

  • 3 ng x 20 = 60 ng/mg in untreated cells

• In treated samples, if 50 $\mu$g total protein contains 71 ng synaptophysin, then the amount of synaptophysin in 1 mg of total protein is:

  • $\frac{1 mg}{50 \mu g}$ or $\frac{1000 \mu g}{50 \mu g}$ = 20

  • 71 ng x 20 = 1420 ng/mg in treated cells

Conclusion

• Growth factor treatment increases synaptophysin gene expression, leading to a 23.7-fold increase in protein levels.

• Calculate fold change in synaptophysin level:

  • Fold Change $= \frac{1420}{60} = 23.7$

Assessing Synaptophysin Activity

• siRNA (small interfering RNA) can assess synaptophysin activity.

• siRNAs are short, double-stranded RNA molecules (~21 base pairs).

• Specific hybridization of siRNA to complementary mRNA causes mRNA degradation, reducing protein levels.

Using siRNA to Manipulate Synaptophysin Levels

• Experiment: Cells transfected with synaptophysin-targeting siRNA show depleted synaptophysin levels.

• Control: Scrambled siRNA control.

Does Synaptophysin Depletion Block Differentiation?

• Experimental Readout: Examine neural cell extensions.

• Experimental Control: Non-differentiated cells; scrambled siRNA.

• Synaptophysin siRNA.

Part 2: Introduction to Clinical Trials

Aims of Clinical Trials

• Improve current treatments.

• Prevent disease.

• Improve screening and diagnostic techniques.

Importance of New Therapies

• New therapies are vital for many diseases.

• Clinical trials translate laboratory research (target discovery and validation) into patient treatment.

• After comprehensive drug development and pre-clinical testing, novel compounds can be tested in patients.

Ultimate Aim of Clinical Trials

• Determine if a new drug is safe and effective.

• Assess whether the drug is more effective or safer than existing treatments.

• Evaluate if the drug is effective for additional diseases.

Information from Animal Models

• Animal models can provide information on drug effectiveness, dosing, scheduling, and potential toxicities.

• Informative mouse models reflect disease initiation and progression.

Clinical Trial Design Considerations

1. What research questions are being addressed?

2. Why should the trial be conducted?

3. Is the trial adequately designed to answer the questions?

Elaborating on Trial Design

1. Research Questions

   • How likely is the trial to change clinical practice?

   • How many future patients will be impacted?

   • Will blood/tissue samples be available for scientific research?

2. Justification for the Trial

   • Has the drug been used in other diseases?

   • Is there strong animal evidence?

   • How strong is the underlying biology?

3. Adequacy of Trial Design

   • Patient selection.

   • Types of controls used.

   • Appropriate measurement/end-point (e.g., overall survival).

Example: Clinical Trial Concept

• A clinician observes that patients with Disease X who are big coffee drinkers have favorable outcomes.

• Research Question: “Does caffeine intake improve the survival of patients with Disease X?”

Controls in Clinical Trials

• Control Arm: Current standard of care.

• Experimental Arm: Receives the new agent.

Controlling Bias in Clinical Trials

1. Randomization

2. Blinding

Methods to Control Bias

1. Randomization: Assigns patients to treatment arms by chance.

2. Blinding: Prevents patients, doctors, and researchers from knowing treatment assignments.

   • Trials can be single-blind (patient only), double-blind (patient and doctor), or triple-blind (patient, doctor, and researcher).

Phase 1 Clinical Trials

• Evaluate safety & determine safe dose range

• Involves small groups of healthy volunteers.

• For anti-cancer drugs, Phase 1 trials generally involve patients who have failed conventional treatments.

• Identifies the most appropriate route for administering drug

• Gradual increasing doses are generally given to successive individuals (dose escalation).

Determining Maximal Tolerated Dose

• The "3+3" model is used to identify the maximal tolerated dose (MTD), defined as the highest dose without significant toxicity.

• Dose-limiting toxicity (DLT) occurs when a patient experiences unacceptable adverse events.

Phase 1 Monitoring

• Drug levels in blood: information on drug kinetics in the body

• Predicted effects of drug on patient: biomarker analysis.

• Toxicity: unwanted side effects

PK and PD Measurements

• Pharmacokinetic studies: What the body does to the drug. E.g. what concentrations are achieved in blood? How long are they maintained?

• Pharmacodynamic studies: What the drug does to the body. E.g. measure change in enzyme activity to show the drug acts on planned target; Toxicity.

Phase 2 Clinical Trials

• Evaluate effectiveness using defined biomarkers/treatment response in patients.

• Further evaluate safety.

• Involve larger groups of patients (40-100).

• Cancer trials normally occur in one specific cancer type.

Phase 3 Clinical Trials

• Further determine effectiveness and side-effects.

• Use strict eligibility criteria (inclusion and exclusion criteria).

• Generally compared with standard treatments.

• Involve large groups of people (more than 200) for statistical validity.

Phase 4 Clinical Trials

• Continued testing after drug approval/marketing to collect information about effects in specific populations and long-term side effects.

Clinical Trials in Practice - Example 1

• Testing efficacy and side-effects of three anti-depressants.

Example 1: Efficacy of 2nd Generation Antidepressants

• Improve current clinical practice and provide better therapies.

• Tricyclic antidepressants (TCAs) are first-generation drugs.

• Selective serotonin re-uptake inhibitors (SSRIs) and serotonin-noradrenalin reuptake inhibitors (SNRIs) are newer agents.

Comparison of Antidepressants

• SSRIs, SNRIs, and TCAs exhibit equivalent antidepressant efficacy.

Side-Effect Profiles

• TCAs and SSRIS/SNRIs display different side-effect profiles.

• Placebo was not used in this study.

Clinical Trials in Practice - Example 2

• Assessing the effectiveness of a new treatment patch for Alzheimer's disease.

Example 2: Alzheimer's Disease Treatment

• A 6-month, double-blind, placebo-controlled study of a skin patch for Alzheimer's disease.

• 1,195 patients were randomized.

• Brain function was measured by assessment of cognitive abilities using the ADAS-cog scale.

Results of Alzheimer's Treatment Trial

• Treatment improved patient cognitive ability over 24 weeks compared to baseline.

Adverse Events

• Comparable side-effects observed across treatment methods.

Enzalutamide for Prostate Cancer

• Enzalutamide is a newly developed treatment for prostate cancer that targets multiple steps in the androgen-receptor-signaling pathway.

• Phase 3, double-blind, placebo-controlled trial.

• 1199 men with castration-resistant prostate cancer after chemotherapy were studied.

• Patients were randomized (2:1) to receive oral enzalutamide (160 mg per day) or placebo.

• The primary end point was overall survival.

Data Interpretation: End Point Analysis

• PSA (Prostate Specific Antigen) is a biomarker for prostate cancer; more PSA indicates a greater disease burden.

Data Interpretation: Side-Effect Profiles

• Table shows adverse events according to grade for enzalutamide and placebo.

Ethical Considerations

1. Collaborative Partnership

2. Social Value

3. Scientific Validity

4. Fair Subject Selection

5. Favorable Risk-Benefit Ratio

6. Independent Review

7. Informed Consent

Ethics Elaborations

1. Collaborative Partnership: Involve the community in planning and overseeing research.

2. Social Value: Lead to improvements in health or advancement in knowledge.

3. Scientific Validity: Conduct research rigorously to produce reliable and valid data.

4. Fair Subject Selection: Scientific objectives should guide inclusion criteria.

5. Favorable Risk-Benefit Ratio: Conduct research consistent with clinical practice standards.

6. Independent Review: Minimize conflicts of interest.

7. Informed Consent: Provide clear, accurate information to participants.

Informed Consent Elements

1. Competence of the subject

2. Disclosure of information to the subject

3. Understanding or comprehension by the subject

4. Voluntariness of the decision

Ethics Committees

• Clinical trials are covered by regulations to protect participants.

• Independent research ethics committees approve medical research involving people.

• These committees include health professionals, patients, lawyers, and members of the public.

• Clinical trials of medicines need authorization from the Medicines and Healthcare products Regulatory Agency (MHRA).

Summary of Clinical Trials

• Clinical trials are conducted mainly to improve clinical practice.

• Numerous types of clinical trials exist; be aware of differences (e.g., placebo-controlled, blinded).

• Statistics are key when interpreting results, and statistical significance is required to draw conclusions.